Shadow detection and building-height estimation using IKONOS data

The spectral confusion between shadow and water (or other dark surfaces) often results in suboptimal urban classification performances, especially from high-resolution satellite imagery (e.g. IKONOS). A classification method was developed to incorporate spatial indices of image objects to improve the shadow/water detection. A number of spatial indices, such as size, shape and spatial neighbour of image objects, were characterized to differentiate water and shadow objects. This generated superior shadow/water detection performance compared to a traditional per-field Extraction and Classification of Homogeneous Objects (ECHO) classification method. The user's accuracies for shadow and water classes were increased to 88% and 92%, compared to 80% and 76% obtained from the traditional ECHO classification approach. Furthermore, an automated approach was developed for shadow-length and corresponding building-height estimation. The accuracy assessment suggested good results for very high buildings, especially for isolated high-rise buildings.

[1]  S. Plummer,et al.  Burnt area detection at global scale using ATSR‐2: The GLOBSCAR products and their qualification , 2004 .

[2]  Narushige Shiode,et al.  3D urban models: Recent developments in the digital modelling of urban environments in three-dimensions , 2000 .

[3]  David A. Landgrebe,et al.  MultiSpec: a tool for multispectral--hyperspectral image data analysis , 2002 .

[4]  M. Herold,et al.  Spatial Metrics and Image Texture for Mapping Urban Land Use , 2003 .

[5]  Lawrence G. Roberts,et al.  Machine Perception of Three-Dimensional Solids , 1963, Outstanding Dissertations in the Computer Sciences.

[6]  Derek R. Peddle,et al.  Remote sensing of biophysical variables in boreal forest stands of Picea mariana , 1996 .

[7]  J. Strobl,et al.  Object-Oriented Image Processing in an Integrated GIS/Remote Sensing Environment and Perspectives for Environmental Applications , 2000 .

[8]  R. Bruce Irvin,et al.  Methods for exploiting the relationship between buildings and their shadows in aerial imagery , 1989, IEEE Trans. Syst. Man Cybern..

[9]  S. Goetz,et al.  IKONOS imagery for resource management: Tree cover, impervious surfaces, and riparian buffer analyses in the mid-Atlantic region , 2003 .

[10]  V. Shettigara,et al.  HEIGHT DETERMINATION OF EXTENDED OBJECTS USING SHADOWS IN SPOT IMAGES , 1998 .

[11]  Henri Maître,et al.  3-D Reconstruction of Urban Scenes from Aerial Stereo Imagery: A Focusing Strategy , 1999, Comput. Vis. Image Underst..

[12]  Alberta Bianchin,et al.  Remote Sensing and Urban Analysis , 2008, ICCSA.

[13]  C. Small.  High spatial resolution spectral mixture analysis of urban reflectance , 2003 .

[14]  David A. Landgrebe,et al.  Signal Theory Methods in Multispectral Remote Sensing , 2003 .

[15]  Julie P. Tuttle,et al.  QuickBird and Hyperion data analysis of an invasive plant species in the Galapagos Islands of Ecuador: Implications for control and land use management , 2008 .

[16]  Clive S. Fraser,et al.  Processing of Ikonos imagery for submetre 3D positioning and building extraction , 2002 .

[17]  F. Agüera,et al.  Detecting greenhouse changes from QuickBird imagery on the Mediterranean coast , 2006 .

[18]  Martin Herold,et al.  The spatiotemporal form of urban growth: measurement, analysis and modeling , 2003 .

[19]  J. C. Tilton.  Image Segmentation By Iterative Parallel Region Growing And Splitting , 1989, 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium,.

[20]  M. Ridd.  Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: comparative anatomy for cities , 1995 .

[21]  Nathan J. Heinert,et al.  Extending satellite remote sensing to local scales: land and water resource monitoring using high-resolution imagery , 2003 .

[22]  J. Shan,et al.  CLASS-GUIDED BUILDING EXTRACTION FROM IKONOS IMAGERY , 2003 .

[23]  Dennis E. Jelinski,et al.  THE RELATIVE IMPORTANCE OF PATCH AREA AND PERIMETER–AREA RATIO TO GRASSLAND BREEDING BIRDS , 1999 .

[24]  J. Townshend,et al.  Detection of land cover changes using MODIS 250 m data , 2002 .

[25]  R. Kettig,et al.  Classification of Multispectral Image Data by Extraction and Classification of Homogeneous Objects , 1976, IEEE Transactions on Geoscience Electronics.

[26]  Marvin E. Bauer,et al.  Integrating Contextual Information with per-Pixel Classification for Improved Land Cover Classification , 2000 .

[27]  Rasmus Fensholt,et al.  Remote Sensing , 2008, Encyclopedia of GIS.

[28]  R. Schowengerdt.  CHAPTER 1 – The Nature of Remote Sensing , 1997 .

[29]  Curtis E. Woodcock,et al.  Nested-hierarchical scene models and image segmentation , 1992 .

[30]  G. Asner,et al.  Canopy shadow in IKONOS satellite observations of tropical forests and savannas , 2003 .

[31]  Manuel A. Aguilar,et al.  Geometric accuracy assessment of the orthorectification process from very high resolution satellite imagery for Common Agricultural Policy purposes , 2008 .